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Towards Deep Physical Reservoir Computing Through Automatic Task Decomposition And Mapping

Oct 25, 2019
Matthias Freiberger, Peter Bienstman, Joni Dambre

* Submitted to the IEEE International Conference on Rebooting Computing 2019; accepted as a poster, will not be presented though 

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Training Passive Photonic Reservoirs with Integrated Optical Readout

Oct 08, 2018
Matthias Freiberger, Andrew Katumba, Peter Bienstman, Joni Dambre

* Accepted for publication in IEEE Transactions on Neural Networks and Learning Systems (TNNLS-2017-P-8539.R1), copyright 2018 IEEE. This research was funded by the EU Horizon 2020 PHRESCO Grant (Grant No. 688579) and the BELSPO IAP P7-35 program [email protected] 11 pages, 9 figures 

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Photonic Delay Systems as Machine Learning Implementations

Jan 12, 2015
Michiel Hermans, Miguel Soriano, Joni Dambre, Peter Bienstman, Ingo Fischer

* Journal of Machine Learning Research, vol. 16, pp. 2081-2097 (2015) 

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Trainable and Dynamic Computing: Error Backpropagation through Physical Media

Jul 24, 2014
Michiel Hermans, Michaël Burm, Joni Dambre, Peter Bienstman

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